在医学领域、可靠性分析和人寿保险市场中, 剩余寿命是重要的研究范畴之一. 因此, 剩余寿命分位数区间的精确估计有着重要的意义. 但是, 在左截断和右删失同时存在的临床数据下, 样本量通常很小, 传统的置信区间构造方法多数不理想, 而且涉及到的估计量方差的计算非常繁琐. 为了避免上述困难, 文章利用 Jackknife-d 方法构造了左截断右删失剩余寿命分位数的置信区间. 同时, 通过蒙特卡罗模拟和实例分析对 Jackknife-d 方法和传统的4种方法进行评价. 模拟结果表明: 小样本下, Jackknife-d 方法得到的置信区间长度最短且覆盖率在大多数情况下都接近于名义水平, 是剩余寿命分位数置信区间构造的一种很好的方法.

In the medical field, reliability analysis and life insurance market, the residual life is one of the important research category. Therefore, it is important to estimate the interval of the residual life accurately. However, under the clinical data with Left-Truncated and Right-Censored, the traditional confidence interval construction method is usually not ideal because of the small sample and the calculation of variance of estimator is very complicated. In order to avoid these difficulties, we use the Jackknife-d method to construct the confidence interval of quantile residual lifetime under left-truncated and right-censored data in this paper. At the same time, we asses five traditional kinds of interval estimation method through examples and Monte Carlo simulation. Simulation results show that under the condition of small samples, the Jackknife-d method is a very good confidence interval estimation method. In most cases it can guarantee that the coverage rate is equal to the nominal significance level and makes the shortest length.